Yearly Traffic Safety Analysis

623 CRASHES IN
IOWA, IA
2025

All metrics benchmarked against2024

In 2025, Jasper County recorded 623 total crashes, a slight decrease of 0.8% from the 628 crashes reported in 2024. While overall crash numbers remained stable, the number of non-collision, single-vehicle crashes increased by 15.2%, from 302 in the prior year to 348 in the current year. Fatalities decreased from 4 to 3, and total injuries fell from 180 to 172.

623

▼ -0.8%was 628

Total Crash Events

3

▼ -25.0%was 4

Persons Killed

172

▼ -4.4%was 180

Persons Injured

3

Fatal Crash Events

Note: "Persons Killed" (3) counts individual fatalities across all crash events. "Fatal" in the severity table below (3) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities.

Source: Iowa Crash Data · ArcGIS Open Data · 2025-01-01 to 2025-12-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall traffic crash trends in Jasper County show a slight decline year-over-year. The total number of crashes decreased by 0.8%, from 628 in 2024 to 623 in 2025. Similarly, total fatalities fell from 4 to 3, and total injuries decreased by 4.4% from 180 to 172.

Vulnerable Road User Casualties

0

Pedestrians Killed

Prior: 0→0.0%

0

Cyclists Killed

Prior: 0→0.0%

3

Motorists Killed

Prior: 4↓-25.0%

0

Other Killed

Prior: 0→0.0%

2

Pedestrians Injured

Prior: 5↓-60.0%

2

Cyclists Injured

Prior: 1↑100.0%

167

Motorists Injured

Prior: 173↓-3.5%

1

Other Injured

Prior: 1→0.0%

Source: Iowa Crash Data · ArcGIS Open Data · 2025-01-01 to 2025-12-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

Temporal crash patterns shifted between the two periods. The peak day for crashes moved from Tuesday (104 crashes) in the prior year to Saturday (108 crashes) in the current year. The peak hour also changed significantly, moving from the 7 a.m. morning commute hour (56 crashes) in 2024 to the 6 p.m. evening hour (41 crashes) in 2025.

Source: Iowa Crash Data · ArcGIS Open Data · 2025-01-01 to 2025-12-31 · Crash date field aggregated by weekday

Source: Iowa Crash Data · ArcGIS Open Data · 2025-01-01 to 2025-12-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

The number of fatal crashes remained unchanged year-over-year, with 3 fatal crashes recorded in both 2025 and 2024. The distribution of injury severity shifted slightly; crashes resulting in serious injuries decreased from 15 to 12, and minor injury crashes fell from 73 to 62. However, crashes involving possible injuries increased from 67 in the prior period to 78 in the current period.

Outcome by Severity (Crash Events)

Fatal3fatal crashes0.5%
→0.0%prior 3
Serious Injury12serious injury crashes1.9%
↓-20.0%prior 15
Minor Injury62minor injury crashes10%
↓-15.1%prior 73
Possible Injury78possible injury crashes12.5%
↑16.4%prior 67
No Injury468no injury crashes75.1%
↓-0.4%prior 470

Source: Iowa Crash Data · ArcGIS Open Data · 2025-01-01 to 2025-12-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Iowa Crash Data · ArcGIS Open Data · 2025-01-01 to 2025-12-31 · Most severe injury per crash record

Top Contributing Factors

Collisions with animals remained the top contributing factor in both periods, though the count decreased by 8.4% from 154 crashes in 2024 to 141 in 2025. The second-ranked factor shifted, with 'Driving too fast for conditions' increasing its count by 52.6% from 38 to 58 crashes, replacing 'Ran off road - straight' (48 crashes) as the number two cause. The count for 'Driver Distraction: Other interior distraction' decreased from 30 to 23 incidents.

Officer-Reported Primary Contributing Cause

Animal141 (22.6%)↓-8.4%prior 154
Driving too fast for conditions58 (9.3%)↑52.6%prior 38
Ran off road - straight48 (7.7%)↑4.3%prior 46
Lost Control45 (7.2%)↑7.1%prior 42
Followed too close34 (5.5%)↑6.3%prior 32
Ran off road - left34 (5.5%)→0.0%prior 34
FTYROW: From stop sign23 (3.7%)→0.0%prior 23
Driver Distraction: Other interior distraction23 (3.7%)↓-23.3%prior 30
Operating vehicle in an reckless, erratic, careless, negligent manner21 (3.4%)↑23.5%prior 17
Other (explain in narrative): Other19 (3%)↓-9.5%prior 21

Source: Iowa Crash Data · ArcGIS Open Data · 2025-01-01 to 2025-12-31 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

While crashes in clear weather and daylight conditions remained the majority and were stable year-over-year, there were notable shifts in adverse conditions. Crashes occurring on snowy road surfaces increased significantly from 29 in 2024 to 51 in 2025. Similarly, the number of crashes in dark, unlighted conditions rose from 88 to 109. The total number of crashes attributed to snow as a weather condition also increased from 28 to 37.

Weather

Clear347 (70.0%)
↓-2.8%prior 357
Cloudy59 (11.9%)
↑5.4%prior 56
Snow37 (7.5%)
↑32.1%prior 28
Rain19 (3.8%)
↓-13.6%prior 22
Blowing Snow15 (3.0%)
↑66.7%prior 9
Severe Winds5 (1.0%)
Fog, smoke, smog5 (1.0%)
→0.0%prior 5
Other (explain in narrative)4 (0.8%)
Freezing rain/drizzle3 (0.6%)
↓-76.9%prior 13
Sleet, hail2 (0.4%)

Source: Iowa Crash Data · ArcGIS Open Data · 2025-01-01 to 2025-12-31 · Weather condition at time of crash

Lighting

Daylight316 (63.1%)
↓-1.6%prior 321
Dark - roadway not lighted109 (21.8%)
↑23.9%prior 88
Dark - roadway lighted35 (7.0%)
↓-10.3%prior 39
Dusk25 (5.0%)
→0.0%prior 25
Dawn11 (2.2%)
↓-26.7%prior 15
Dark - unknown roadway lighting5 (1.0%)
↓-58.3%prior 12

Source: Iowa Crash Data · ArcGIS Open Data · 2025-01-01 to 2025-12-31 · Lighting condition field

Road Surface

Dry357 (71.5%)
↓-4.3%prior 373
Snow51 (10.2%)
↑75.9%prior 29
Wet42 (8.4%)
↓-2.3%prior 43
Ice/frost26 (5.2%)
↓-10.3%prior 29
Gravel18 (3.6%)
↑80.0%prior 10
Slush4 (0.8%)
↓-20.0%prior 5
Water (standing or moving)1 (0.2%)

Source: Iowa Crash Data · ArcGIS Open Data · 2025-01-01 to 2025-12-31 · Road surface condition field

Vehicles & Demographics

The top vehicle makes involved in crashes remained consistent, with 'CHEV' (135) and 'FORD' (121) leading in the current period, down from 148 and 137 respectively in the prior year. An analysis of persons involved shows a notable increase in the 16-20 age group, which grew from 108 individuals in 2024 to 131 in 2025. Conversely, involvement for the 35-44 age group saw a slight decrease from 161 to 157 individuals.

Top Vehicle Makes (936 vehicles)

1
CHEV135 (14.4%)
↓-8.8%prior 148
2
FORD121 (12.9%)
↓-11.7%prior 137
3
HOND46 (4.9%)
↑27.8%prior 36
4
GMC43 (4.6%)
↑79.2%prior 24
5
CHEVROLET43 (4.6%)
↓-20.4%prior 54
6
TOYT40 (4.3%)
↑11.1%prior 36
7
DODG40 (4.3%)
↑33.3%prior 30
8
JEEP39 (4.2%)
↑14.7%prior 34
9
NISS38 (4.1%)
↑35.7%prior 28
10
FREIGHTLINER29 (3.1%)
↑11.5%prior 26

Source: Iowa Crash Data · ArcGIS Open Data · 2025-01-01 to 2025-12-31 · Vehicle unit records

82 persons with unknown or unrecorded age excluded from age chart.

Sex Distribution (580 persons with recorded sex)

Male387 (66.7%)
↑10.6%prior 350
Female193 (33.3%)
↓-4.0%prior 201

Source: Iowa Crash Data · ArcGIS Open Data · 2025-01-01 to 2025-12-31 · Person-level records linked to crash events

Data Sources & Methodology

Primary Data Source

All crash data in this report is sourced from Iowa Crash Data, accessed programmatically via the ArcGIS Open Data API (SODA). This dataset contains official police-reported motor vehicle traffic crash records maintained by the reporting jurisdiction's law enforcement agency. Records are published to the open data portal by the municipality and are subject to the portal's terms of use.

Data Retrieval

  • Access method: ArcGIS Open Data API (SoQL queries)
  • Data format: Structured JSON via REST API
  • Record types queried: Crash events, person records, and vehicle unit records
  • Date filter applied: 2025-01-01 through 2025-12-31
  • Report generated: September 9, 2026

Data Coverage

  • Reporting period: 2025-01-01 through 2025-12-31 (365 days)
  • Geographic scope: iowa, IA
  • Total crash records analyzed: 623
  • Total persons involved: 970
  • Total vehicles involved: 936

Analytical Methodology

  • Severity classification: Uses the KABCO injury scale (K=Fatal, A=Incapacitating injury, B=Non-incapacitating injury, C=Possible injury, O=No injury/property damage only), the standard classification in U.S. Model Minimum Uniform Crash Criteria (MMUCC). Severity is assigned per crash event based on the most severe injury in that crash. A single fatal crash (K) may involve multiple fatalities; therefore the "Persons Killed" count in the headline KPIs may differ from the "Fatal" crash count in the severity breakdown.
  • Contributing factors: Reflect the officer-determined primary contributory cause recorded at the time of the crash report. These are preliminary determinations and may not reflect final investigation findings.
  • Hit-and-run classification: Based on the hit-and-run indicator field in the official crash report, as determined by the responding officer at the scene.
  • Temporal analysis: Day-of-week and hour-of-day distributions are computed from the crash date/time timestamp in each record.
  • Demographics: Age and sex distributions are drawn from person-level records linked to each crash event. A single crash may involve multiple persons.
  • Vehicle data: Make information is drawn from vehicle unit records linked to each crash event.
  • AI commentary: Narrative sections are generated by Google Gemini (large language model) based on the structured data. Commentary is descriptive, not predictive, and should not be interpreted as expert opinion.

Limitations & Disclaimers

  • Only crashes reported to and documented by law enforcement are included. Minor incidents, unreported crashes, and near-misses are not captured in this dataset.
  • Data reflects conditions at the time of the initial police report and may be subject to subsequent corrections, reclassifications, or supplements by the reporting agency.
  • Open data portal records may experience a publication lag - recently occurring crashes may not yet appear in the dataset at the time of report generation.
  • AI-generated commentary is produced by a large language model and is intended to highlight patterns in the data. It does not constitute legal, medical, or professional analysis.
  • Percentages are calculated from reported data and are subject to rounding.

Non-Affiliation Disclosure

This report is produced independently by ThatCarHitMe.com (Injuria.ai). It is not affiliated with, endorsed by, or produced in partnership with any law enforcement agency, municipal government, state department of transportation, or the National Highway Traffic Safety Administration (NHTSA). Data is sourced from publicly available government open data portals.

Data License

The underlying crash data is provided under the municipality's Open Data Terms of Use and is made available to the public for unrestricted use. This analysis and report is © 2026 Injuria.ai and may be cited with attribution using the suggested citation below.

Corrections & Feedback

If you believe any data in this report is inaccurate or have questions about our methodology, please contact: data@injuria.ai. We are committed to accuracy and will issue corrections promptly.

Suggested Citation

ThatCarHitMe.com (Injuria.ai). "iowa, IA Crash Intelligence Report: 2025." Published September 9, 2026. Reporting period: 2025-01-01 to 2025-12-31. Data source: Iowa Crash Data, ArcGIS Open Data. Available at: https://thatcarhitme.com/crash-data/iowa/statewide/2025-annual-report

About the Publisher

ThatCarHitMe.com is a crash data intelligence platform developed by Injuria.ai, a legal technology company specializing in traffic safety analytics. We aggregate and analyze publicly available government crash data to produce structured intelligence reports for communities, researchers, journalists, and legal professionals. Our reports combine programmatic data retrieval from official open data portals with AI-assisted narrative analysis.

Questions about this report's data or methodology: data@injuria.ai

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